Wei Cheng


Researcher
Data Science
& Systems Research

NEC Laboratories America, Inc.
4 Independence Way, Suite 200
Princeton, NJ  08540
Fax: +1 609-951-2482
 
Email: weicheng "AT" nec-labs.com
Homepage: sites.google.com/site/weichengunc/
  • A Flexible Deep Embedding Approach for Anomaly Detection in Dynamic Networks.
    Wenchao Yu, *Wei Cheng, Charu Aggarwal, Kai Zhang, Haifeng Chen, Wei Wang.
    The Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD’18), 2018. (Long Oral Presentation)

  • Learning Deep Network Representations with Adversarially Regularized Autoencoders.
    Wenchao Yu, Cheng Zheng, *Wei Cheng, Charu Aggarwal, Dongjing Song, Bo Zong, Haifeng Chen, Wei Wang.
    The Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD’18), 2018. (Long Oral Presentation)

  • Deep r-th Root Rank Supervised Joint Binary Embedding for Multivariate Time Series Retrieval
    Dongjing Song, Ning Xia, Wei Cheng, Haifeng Chen, Dacheng Tao.
    The Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD’18), 2018. (Long Oral Presentation)

  • DBSDA: Lowering the Error Bound of Sparse Linear Discriminant Analysis via Model De-Biasing.
    Haoyi Xiong, Wei Cheng, Wenqing Hu, Jiang Bian, Zhishan Guo.
    IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2018.

  • Analysis of Shared Heritability in Common Disorders of the Brain.
    Schizophrenia Working Group of the Psychiatric Genomics Consortium (PGC-SCZ).
    Science, 2018.
  • Deep Autoencoding Gaussian Mixture Model for Unsupervised Anomaly Detection.
    Bo Zong, Qi Song, Martin Renqiang Min, Wei Cheng, Cristian Lumezanu, Daeki Cho, Haifeng Chen.
    Sixth International Conference on Learning Representations (ICLR), 2018.
  • Scaling up Kernel SVM on Limited Resources: A Low-rank Linearization Approach.
    Liang Lan, Zhuang Wang, Wei Cheng, Kai Zhang.
    IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2018.
  • Co-Regularized Deep Multi-Network Embedding.
    Jingchao Ni, Shiyu Chang, Xiao Liu, Wei Cheng, Haifeng Chen, Dongkuan Xu and Xiang Zhang.
    Proceedings of the International Conference on World Wide Web (WWW), 2018.
  • Identifying and Quantifying Nonlinear Structured Relationships in Complex Manufactural Systems.
    T. Xu, T. Yan, D. Song, Wei Cheng, H. Chen, G. Jiang and J. Bi
    IEEE International Conference on Big Data (Big Data 2017), Boston, MA, December, 2017.
  • ComClus: A Self-Grouping Framework for Multi-Network Clustering. 
    Jingchao Ni, Wei Cheng, Wei Fan, Xiang Zhang.
    Transactions on Knowledge and Data Engineering (TKDE), 2017.
  • Link Prediction with Spatial and Temporal Consistency in Dynamic Networks. 
    Wenchao Yu, *Wei Cheng, Wei Wang, Charu C Aggarwal, Haifeng Chen. 
    Proc. 27th Intl. Joint Conf. on Artificial Intelligence (IJCAI), 2017. (PDF)
  • A Dual-Stage Attention-Based Recurrent Neural Network for Time Series Prediction. 
    Yao Qin, Dongjin Song, Haifeng Chen, Wei Cheng, Geoff Jiang, Garrison Cottrell. 
    Proc. 27th Intl. Joint Conf. on Artificial Intelligence (IJCAI), 2017. (PDF)
  • Many Heads are Better than One: Local Community Detection by the Multi-Walker Chain. 
    Yuchen Bian, Jingchao Ni, Wei Cheng, Xiang Zhang.
    The 2017 edition of the IEEE International Conference on Data Mining series (ICDM), 2017. (Best Paper Nomination)
  • Ranking Causal Anomalies by Modeling Local Propagations on Networked Systems
    Jingchao Ni, *Wei Cheng, Kai Zhang, Dongjin Song, Tan Yan, Haifeng Chen, Xiang Zhang.
    The 2017 edition of the IEEE International Conference on Data Mining series (ICDM), 2017.
  • Multi-Party Sparse Discriminant Learning. 
    Jian Bian, Haoyi Xiong, Wei Cheng, Yanjie Fu, Wenqing Hu, Zhishan Guo. 
    The 2017 edition of the IEEE International Conference on Data Mining series (ICDM), 2017.
  • AWDA: An Adaptive Wishart Discriminant Analysis. 
    Haoyi Xiong, Wei Cheng, Wenqing Hu, Jiang Bian, and Zhishan Guo.
    The 2017 edition of the IEEE International Conference on Data Mining series (ICDM), 2017.
  • Low-rank Decomposition Meets Kernel Learning: A Generalized Nystrom Method . 
    Liang Lan, Kai Zhang, Hancheng Ge, Wei Cheng, Jun Liu, Andreas Rauber, Xiao-Li Li, Jun Wang, Hongyuan Zha. 
    Artificial Intelligence, 2017.
  • Ranking Causal Anomalies for System Fault Diagnosis via Temporal and Dynamical Analysis on Vanishing Correlations. 
    Wei Cheng, Jingcao Ni, Kai Zhang, Haifeng Chen, Guofei Jiang, Yu Shi, Xiang Zhang, Wei Wang. 
    Transactions on Knowledge Discovery from Data (TKDD), 2017. (Paper)(Best Papers of KDD 2016)
  • Self-Grouping Multi-Network Clustering. 
    Jingcao Ni, Wei Cheng, Wei Fan, Xiang Zhang. 
    In Proceedings of the IEEE International Conference on Data Mining series (ICDM'16), 2016. (Paper)(Appendix)
  • Ranking Causal Anomalies via Temporal and Dynamical Analysis on Vanishing Correlations.
    Wei Cheng, Kai Zhang, Haifeng Chen, Guofei Jiang, Zhengzhang Chen, Wei Wang.
    In Poceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining(SIGKDD), 2016. (Video)(Award)(paper)(code)(Best Paper Runner Up Award)(Award Plaque)
  • Contribution of copy number variants to schizophrenia from a genome-wide study of 41,321 subjects.
    Schizophrenia Working Group of the Psychiatric Genomics Consortium (PGC-SCZ).
    Nature Genetics, 2016.(paper)
  •  Genetic influences on schizophrenia and subcortical brain volumes: large-scale proof-of-concept and roadmap for future studies.
    Schizophrenia Working Group of the Psychiatric Genomics Consortium (PGC-SCZ).
    Nature Neurosci, 2016.(paper)
  • Robust Framework on Multi-Network Clustering via Joint Cross-Domain Cluster Alignment.
    Rui Liu, Wei Cheng, Hanghang Tong, Wei Wang, Xiang Zhang.
    Knowledge and Information Systems (KAIS), 2016. (Joint First Author, one of the best papers in ICDM'15 selected to KAIS journal)
  • Sparse Regression Models for Unraveling Group and Individual Associations in eQTL Mapping. 
    Wei Cheng, Yu Shi, Xiang Zhang, Wei Wang.
    BMC Bioinformatics. 2016. (PDF)(Appendix)
  • CGC: A Flexible and Robust Approach to Integrating Co-Regularized Multi-Domain Graph for Clustering. 
    Wei Cheng, Zhishan Guo, Xiang Zhang, Wei Wang. 
    Transactions on Knowledge Discovery from Data (TKDD), 2016. (PDF)
  • Robust Methods for Expression Quantitative Trait Loci Mapping. 
    Wei Cheng, Xiang Zhang, Wei Wang.
    Big Data Analytics in Genomics. Springer (New York), 2016. (PDF)
  • Toward Robust Group-Wise eQTL Mapping via Integrating Multi-Domain Heterogeneous Data. 
    Wei Cheng.
    Ph.D. Thesis, University of North Carolina at Chapel Hill, 2015. (PDF)
  • Robust Multi-Network Clustering via Joint Cross-Domain Cluster Alignment.
    Rui Liu, Wei Cheng, Hanghang Tong, Wei Wang, Xiang Zhang. 
    Proceedings of the IEEE International Conference on Data Mining (ICDM), 2015. (paper) (Joint First Author, Best Paper Nomination)
  • Modeling linkage disequilibrium increases accuracy of polygenic risk scores.
    Schizophrenia Working Group of the Psychiatric Genomics Consortium (PGC-SCZ).
    The American Journal of Human Genetics, 2015.
  • HICC: An Entropy Splitting Based Framework for Hierarchical Co-Clustering.
    Wei Cheng, Xiang Zhang, Feng Pan, Wei Wang. 
    Knowledge and Information Systems(KAIS), 2015. (paper)(code)
  • Fast and Robust Group-Wise eQTL Mapping Using Sparse Graphical Models.
    Wei Cheng, Yu Shi, Xiang Zhang, Wei Wang.
    BMC Bioinformatics , 2015.(paper)
  • Biological Insights From 108 Schizophrenia-Associated Genetic Loci.
    Schizophrenia Working Group of the Psychiatric Genomics Consortium (PGC-SCZ).
    Nature, 2014. (paper).
  • Partitioning heritability of regulatory and cell-type-specific variants across 11 common diseases.
    Schizophrenia Working Group of the Psychiatric Genomics Consortium (PGC-SCZ).
    The American Journal of Human Genetics, 2014.
  • Graph Regularized Dual Lasso for Robust eQTL Mapping. 
    Wei Cheng, Xiang Zhang, Zhishan Guo, Yu Shi and Wei Wang.
    In Proceedings of the 22nd Annual International Conference on Intelligent Systems for Molecular Biology (ISMB) , 2014, (paper)(slides)(code).
  • Flexible and Robust Co-Regularized Multi-Domain Graph Clustering.
    Wei Cheng, Xiang Zhang, Zhishan Guo, Yubao Wu, Patrick Sullivan and Wei Wang.
    In Poceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD), Chicago, 2013.(PDF) (slides) (poster)(matlab code&data)(C++ code).
  • Searching Dimension Incomplete Databases.
    Wei Cheng, Xiaoming Jin, Jiantao Sun, Xuemin Lin, Xiang Zhang, Wei Wang.
    Transactions on Knowledge and Data Engineering (TKDE), 2013. (PDF)
  • Grid-based Clustering.
    Wei Cheng, Wei Wang, Sandra Batista. 
    In "Data Clustering: Algorithms and Applications"(Eds: Charu C. Aggarwal, Chandan K. Reddy), Chapter 6, CRC Press, 2012. (PDF)
  • Inferring novel associations between SNP sets and gene sets in eQTL study using sparse graphical model.
    Wei Cheng, Xiang Zhang, Yubao Wu, Xiaolin Yin, Jing Li, David Heckerman and Wei Wang. 
    In Proceedings of the third ACM Conference on Bioinformatics, Computational Biology and Biomedicine (ACM-BCB 2012), Orlando, Florida 2012. (PDF) (Slides)
  • Hierarchical Co-Clustering Based on Entropy Splitting.
    Wei Cheng, Xiang Zhang, Feng Pan, Wei Wang.
    In Proceedings of the 21st ACM Conference on Information and Knowledge Management (ACM CIKM 2012), Maui, HI 2012. (PDF)(CODE) (Slides)
  • Learning transcriptional regulatory relationship using sparse graphical models.
    Xiang Zhang, Wei Cheng, Jennifer Listgarten, Carl Kadie, Shunping Huang, Wei Wang, David Heckerman.
    PLoS One , 2012. (PDF) (Joint First Author)
  • Dual Transfer Learning.
    Mingsheng Long, Jianmin Wang, Guiguang Ding, Wei ChengXiang ZhangWei Wang . 
    In Proceedings of the 12th SIAM International Conference on Data Mining (SIAM SDM 2012). Anaheim, CA USA, April 2012. (PDF) (slides)(Best Paper Nomination)
  • Measuring Opinion Relevance in Latent Topic Space.
    Wei Cheng, Xiaochuan Ni, Jian-Tao Sun, Xiaoming Jin, Hye-chung Kum, Xiang ZhangWei Wang
    In Proceedings of the Third IEEE International Conference on Social Computing (IEEE SocialCom 2011) MIT, MA USA, 2011. (PDF) (Slides)
  • Transfer Learning via Cluster Correspondence Inference.
    Mingsheng Long, Wei Cheng, Xiaoming Jin, Jianmin WangDou Shen.
    In Proceedings of the 10th IEEE International Conference on Data Mining (IEEE ICDM 2010 ). Sydney, Australia, December 2010. (PDF) (Slides)
  • Probabilistic Similarity Query on Dimension Incomplete Data,
    Wei Cheng, Xiaoming Jin, Jian-Tao Sun.
    In Proceedings of the 9th IEEE International Conference on Data Mining (IEEE ICDM 2009). Florida, Miami, December 2009. (PDF) (Slides)